Twenty-Five Years With the Biopsychosocial Model of Low Back Pain—Is It Time to Celebrate? A Report From the Twelfth International Forum for Primary Care Research on Low Back Pain
Bibliographic record
Abstract
STUDY DESIGN: An integrated review of current knowledge about the biopsychosocial model of back pain for understanding etiology, prognosis, and interventions, as presented at the plenary sessions of the XII International Forum on LBP Research in Primary Care (Denmark; October 17-19, 2012). OBJECTIVE: To evaluate the utility of the model in reference to rising rates of back pain-related disability, by identifying (a) the most promising avenues for future research in biological, psychological, and social approaches, (b) promising combinations of all 3 approaches, and (c) obstacles to effective implementation of biopsychosocial-based research and clinical practice. SUMMARY OF BACKGROUND DATA: The biopsychosocial model of back pain has become a dominant model in the conceptualization of the etiology and prognosis of back pain, and has led to the development and testing of many interventions. Despite this back pain remains a leading source of disability worldwide. METHODS: The review is a synthesis based on the plenary sessions and discussions at the XII International Forum on LBP Research in Primary Care. The presentations included evidence-based reviews of the current state of knowledge in each of the 3 areas (biological, psychological, and social), identification of obstacles to effective implementation and missed opportunities, and identification of the most promising paths for future research. RESULTS: Although there is good evidence for the role of biological, psychological, and social factors in the etiology and prognosis of back pain, synthesis of the 3 in research and clinical practice has been suboptimal. CONCLUSION: The utility of the biopsychosocial framework cannot be fully assessed until we truly adopt and apply it in research and clinical practice. LEVEL OF EVIDENCE: N/A.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.070 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".